cluster_gen_separate {lsasim} | R Documentation |
Generate cluster samples with individual questionnaires
Description
This is a sub-function of 'cluster_gen' that performs cluster sampling, with the twist that each cluster level has its own questionnaire.
Usage
cluster_gen_separate(
n_levels,
n,
N,
sum_pop,
calc_weights,
sampling_method,
cluster_labels,
resp_labels,
collapse,
n_X,
n_W,
cat_prop,
c_mean,
sigma,
cor_matrix,
rho,
theta,
whitelist,
verbose,
...
)
Arguments
n_levels |
number of cluster levels |
n |
numeric vector with the number of sampled observations (clusters or subjects) on each level |
N |
list of numeric vector with the population size of each *sampled* cluster element on each level |
sum_pop |
total population at the lowest level (sampled or not) |
calc_weights |
if 'TRUE', sampling weights are calculated |
sampling_method |
can be "SRS" for Simple Random Sampling or "PPS" for Probabilities Proportional to Size, "mixed" to use SRS for students and PPS otherwise or a vector with the sampling method for each level |
cluster_labels |
character vector with the names of each cluster level |
resp_labels |
character vector with the names of the questionnaire respondents on each level |
collapse |
if 'TRUE', function output contains only one data frame with all answers |
n_X |
list of 'n_X' per cluster level |
n_W |
list of 'n_W' per cluster level |
cat_prop |
list of cumulative proportions for each item. If |
c_mean |
vector of means for the continuous variables or list of vectors for the continuous variables for each level |
sigma |
vector of standard deviations for the continuous variables or list of vectors for the continuous variables for each level |
cor_matrix |
Correlation matrix between all variables (except weights) |
rho |
estimated intraclass correlation |
theta |
if |
whitelist |
used when 'n = select(...)', determines which PSUs get to generate questionnaires |
verbose |
if 'TRUE', prints output messages |
... |
Additional parameters to be passed to 'questionnaire_gen()' |
See Also
cluster_gen cluster_gen_together